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Resilience has emerged as a crucial measure of a company’s ability to withstand challenges in the current complex business environment. However, prior research indicates that employee diversity may not consistently lead to a positive impact on corporate resilience. This paper investigates the impact of diversity on resilience in the face of various external crises by examining the performance of Chinese listed companies during the 20-year period following their accession to the World Trade Organization. Employee diversity is operationalized in this study by changes in the number of employees in non-core departments, while resilience is represented by the fluctuation of the stock price minus the industry range fluctuation. Employing a fixed-effect model to analyze 20-year panel data, we find that an increase in employee diversity does not always lead to improved corporate resilience during external crises. The purpose of this paper is to examine the relationship between employee diversity and resilience in the face of different external shocks and explore why diversity may fail to enhance resilience during such circumstances.

The COVID-19 outbreak in early 2020 not only had a significant impact on China at the macro level, but also triggered changes in public psychology and irrational behavior at the individual level, one of the typical features of which was the panic buying behavior exhibited by residents during the outbreak. Based on Perceived Risk theory, emotion infection theory and information processing theory, this paper investigates the influence of herd mentality on panic buying behavior and the mediating role of Perceived Risk and information overload, and validates the model by collecting data from 326 residents through a questionnaire. The results show that herding mentality, Perceived Risk, and information overload all have positive effects on panic buying; Perceived Risk and information overload partially mediate the effect between herding mentality and panic buying, and information overload carries more mediating effects. These results suggest that higher levels of herding, Perceived Risk, and information overload can intensify individuals’ panic buying and cause further irrational buying behavior. In response to the findings, this paper also proposes countermeasures to deal with panic buying from three aspects: individuals, media, and government.

Both ICT and internet have become a vital part of citizens’ daily lives. In fact, many aspects of cities, including culture, economy, education have become closely linked to ICT. Accordingly, the concept of the smart city has emerged to attract the interest of governments, companies, educational institutions and Universities [1]. In Morocco, most universities or higher education institutions have always been interested in keeping up with the fast-paced world of technology and integrate ICT in mainstream education. However, most attempts to initiate smart universities is always faced with a series of challenges and constraints. Most of which are related to lack of infrastructure, students’ and professors’ lack of technological readiness, and socio-economic inequality among students. Most recently, due to COVID-19, universities are forced to resort to emergency remote learning and scramble different options of e-learning as a dire need to tackle the current educational crisis which creates a certain chaos due to lack of readiness to an advanced technological application. This paper is an attempt to discuss the challenges posed and opportunities offered using e-learning to deal with the new normal (Covid-19) in different educational levels in general and higher education in particular. Significantly, this paper reviews most of that has been said about online learning, describes some of the conducted empirical studies, and calls for implementing e-learning as an innovative teaching strategy for smart universities.

This article aims to explore how the COVID-19 pandemic affects students’ learning and to determine the most effective way for universities to manage the epidemic while continuing their regular operations. The study also aims to identify any areas where universities’ behavior during the COVID-19 pandemic or any similar crises in the future may need to be improved. The primary purpose of any university is to carry out academic activities, and this research focuses on how to do so effectively and efficiently. The study reports that COVID-19 has hurt graduate programs, internships, internal and external assessments, and student learning after reviewing the literature. However, the pandemic has also allowed universities to improve their internet and ICT infrastructure and provide the necessary skills for their workforce to deliver effective learning. This was done in addition to mitigating the learning challenges brought on by COVID-19. While the article focuses on analyzing the body of literature about the impact of COVID-19 on student learning during the pandemic, it also identifies several areas that need further investigation. To provide an integrated approach to managing university academic business while combating the pandemic, research must be done from the viewpoint of teachers, lecturers, administrators, and other parties. The first chapter of the study covers the primary data and history of COVID-19. COVID-19 began in late 2019 and rapidly spread globally. The World Health Organization classified COVID-19 as a pandemic in early 2020. COVID-19 has affected every aspect of life, including schooling. The second chapter examines the impact of the pandemic on students' learning, as well as the containment and preventative measures implemented by the relevant authorities to halt the virus’s spread. This chapter covers the enrollment of students before and after COVID-19, the teaching strategies used to reduce the risk of infection and ensure student learning, the validity and efficiency of student assessments, and other experiences, including stress on a physical, emotional, and financial level. It also discusses internships and jobs and outlines some benefits and opportunities associated with efficient learning as a means of advancing. The final chapter emphasizes the limitations of the paper's topic under discussion.

In a steel plant, one of the critical tasks of plant logistics is the transportation of the finished products. A steel company transportation system generally consists of a fleet of load-carrying trailers and rail, which are used to transport finished goods. In this paper, a two-stage mathematical model is developed for an Indian company that helps with strategic planning of the supply of finished construction steel (TMT Bar and Structural Steel) from multiple plant locations to the stockyards and then to the distributors. The transportation cost depends on various factors like the type of transportation mode, loading & unloading charges, and other fixed expenses. The steel demand also varies based on the season and other external factors like COVID-19, government policies, and so forth. The model proposed in the present research facilitates cost-effective network planning by achieving the most appropriate dispatching method considering various factors operating in multiple stages using a mixed fleet of trailers and rail. The model’s key objective is to optimize the transportation cost and demand for construction steel.

The Covid-19 Pandemic, with its first ever reported case in the Wuhan province of China in the year 2019, has led to a newfound global demand for Medical Oxygen supply at a sudden and unprecedented rate. In India, people battled to breathe as oxygen demand shot up with a sudden surge in COVID-19 cases the year 2020. The additional requirement of oxygen was tried to be fulfilled by various means such as oxygen generators installed at hospitals, transported medical as well as Industrial liquid oxygen, oxygen cylinder and oxygen concentrator. During the Covid-19 outbreak, large crowds gathered outside hospitals, and many patients were treated at home, breathing with the assistance of an oxygen concentrator and cylinders. However, cylinders must be refilled, whereas unlimited supply of medical grade oxygen can be obtained by oxygen concentrator if a power backup is maintained. In addition to this, safety, cost and size are the additional features of oxygen concentrator. It is a boon for the sufferer at the initial stage or even after treatment of covid-19, which is made available anywhere. In this paper, an attempt has been made to study an oxygen concentrator in which the principle of Pressure Swing Adsorption (PSA) method is used for oxygen separation. In addition to this, some trends of recently evolved developments in oxygen concentration methods are also reviewed for the readers’ reference. This effort will help to develop the oxygen concentrator to fulfill the demand of oxygen at local level during the waves of Covid or similar incidences in future.

Data analysis is very sophisticated tool in recent corona virus pandemic to find the trend of spreading pattern for controlling the infection. In this perspective, predictive analytics can be useful for data analysis to forecast the corona virus pandemic. This paper presents the infection pattern of corona virus disease, termed as COVID-19 in top seven states in India. Prophet Algorithm forecasting model was used to analyze state-wise spreading pattern of corona virus disease with respect to confirmed, deaths and cured cases. This predictive model can be very helpful to government and health care communities to combat this deadly virus by initiating suitable actions to control its spread.

The analysis of Moroccan companies’ resilience is of extreme importance, especially in times of crisis. Covid-19 is an example that revealed the shortcomings and weaknesses of most Moroccan companies when it comes to crisis anticipation and management. In this paper, we have chosen to study the case of companies from two important industries in Morocco: agriculture and tourism. The aim is to investigate the level of preparation of these companies for the crisis, their reaction during the pandemic, and the lessons learned to be more resilient. The two case studies show a lack of preparation due to the sudden occurrence of the crisis, however, the impact was different between the two, due to the nature of the activity and the business size; one is a small local company (agriculture) and the other is the branch of a multinational one (hospitality). The study case results show that most of the companies’ functions were impacted (procurement, production, sales, etc.). These companies’ reaction was different as well, from acting on the inventories and managing the production (Agriculture Company) to optimizing human and financial resources and exploring swinging activities (Hospitality Company). Both got government support. The two companies agreed that the most important aspect of resilience is finance resilience which considers the wider definition of “generating value” that includes in addition to the turnover, the environment, the social and governance aspects (commonly known as ESG). According to the case study, for better resilience in the future, a greater awareness of the importance of financial & environmental resilience is key, and the use of performance metrics and indicators (KPIs) is the way, to allow close monitoring of the activity to be alarmed in advance and strategically anticipate big crises.

Strict control taken in response to public health emergencies (PHEs) can hinder fresh products supply, while stock-outs and the risk of epidemics can increase fresh products demand. To explore the interrelationship between outbreak control measures and the availability of fresh products, this paper establishes a dynamic synergistic model of epidemic transmission subsystem and fresh products supply-consumption subsystem based on system dynamics (SD). Taking the spread of COVID-19 in Shanghai from March to May 2022 as the actual background, the impact of different storage strategies and control measures on epidemic prevention and material supply was quantitatively evaluated. The results show that risk transmission factor (RTF) affects the number of infections and the intensity of community control contributes to controlling the spread of the epidemic, but it can continue to affect fresh product supply security. Therefore, increasing fresh product protection inputs and reducing in-transit time can reduce fresh product losses and improve fresh product supply security under PHEs. The findings can enable fresh products to effectively match supply and demand under PHEs, mitigate the impact of epidemic risks and provide decision support for relevant retailers.

The COVID-19 outbreak has a psychological impact on international students in China. Public psychological crisis prevention and intervention, and a timely economic and social restoration have become increasingly important. Focusing on international students in China, this paper summarizes different types of psychological issues and their causes after surveying the students’ mental health status and behavior changes. It proposes a systematic approach to address international students’ mental issues from three dimensions including government management, university education, and social support. It establishes the education model for international students’ mental health during the COVID-19 pandemic.

The term “Black Swan” by N. Taleb (Taleb, 2007) well illustrates a sudden, negatively manifesting itself in relation to the surrounding world factor. Actively used since 2015, this concept implies a shock impact on economic and production systems, which include transport and logistics systems. COVID-19 and its negative manifestations are a good example of such a 'black swan’. The serious crisis of the world economic system, which began in February-March 2020 and lasted about 450-600 days, was caused by a total restriction of elementary physical contacts between people and any manifestations of their pedestrian and transport mobility associated with it. The widespread lockdowns served this very purpose. However, lockdowns varied across countries in terms of timing, duration, methodological approaches, the strength of restrictions, and control measures. As a result, the mobility of the urban population varied with the influence of the external environment and was not identical in different cities. This paper presents the results of comparative studies of the urban population mobility dynamics in three European cities: two cities of one country – Moscow and St. Petersburg, and another European capital – Amsterdam. At the same time, the goal was to identify the urban mobility country patterns similarity during the period of COVID restrictions. Two tasks were solved: a cross-country comparison of trends in urban population mobility during 2020-2021 and a comparison of trends in population mobility in two cities of the same country.

Carrying out large-scale structural transformations of both the entire Russian economy and its individual actors is one of the most important tasks of the current stage of national development. The urgency of this problem has increased dramatically during the COVID-19 pandemic. The purpose of this paper is to identify the most significant factors in the pandemic that affect the economic growth of Russia’s regions and reduce territorial inequality. The use of methods of comparative and economic-statistical analysis made it possible to establish that the most important independent factor in the development of a region is the structure of the economy and such a factor that ensures it as the regional structural (industrial) policy. It has been substantiated that structural modernization is the basis for pursuing a non-contradictory short- and long-term policy to reduce interterritorial inequality. A particularly negative impact of the pandemic on regions with a low level of development of the real sector and overdevelopment of the service sector has been revealed.

Covid-19 disease has confronted the world with an unprecedented health crisis, faced with its quick spread, the health system is called upon to increase its vigilance. So, it is essential to set up a quick and automated diagnosis that can alleviate pressure on health systems. Many techniques used to diagnose the covid-19 disease, including imaging techniques, like computed tomography (CT). In this paper, we present an automatic method for COVID-19 Lung Infection Segmentation from CT Images, that can be integrated into a decision support system for the diagnosis of covid-19 disease. To achieve this goal, we focused to new techniques based on artificial intelligent concept, in particular the uses of deep convolutional neural network, and we are interested in our study to the most popular architecture used in the medical imaging community based on encoder-decoder models. We use an open access data collection for Artificial Intelligence COVID-19 CT segmentation or classification as dataset, the proposed model implemented on keras framework in python. A short description of model, training, validation and predictions is given, at the end we compare the result with an existing labeled data. We tested our trained model on new images, we obtained for Area under the ROC Curve the value 0.884 from the prediction result compared with manual expert segmentation. Finally, an overview is given for future works, and use of the proposed model into homogeneous framework in a medical imaging context for clinical purpose.

Covid-19 is a very extraordinary case not only in one country but all countries in the world. The number of deaths caused by Covid-19 is very large and the rate of spread of this disease is very high and fast. In this paper, we perform an analysis of a covid-19 epidemic model. This model is a development of the SEIR model in general which is equipped with a Quarantine (Q), Fatality (F) compartment, and there is a separation between detected and undetected infected people (I). Our analysis shows that there are two equilibria, namely, disease free equilibrium and endemic equilibrium. by using, Lyapunov function, we demonstrated that disease free is globally asymptotically stable if R0 < 1, and disease-free becomes unstable if R0 > 1. This result reveal that the intervention of infection rate and quarantine process are important to control and achieve global stability of disease-free equilibrium